Title of thesis: A PERFORMANCE CHARACTERIZATION OF KERNEL-BASED ALGORITHMS FOR ANOMALY DETECTION IN HYPERSPECTRAL IMAGERY Hirsh Goldberg Master of Science, 2007 Thesis directed by: Professor Rama Chellappa Department of Electrical Engineering This thesis provides a performance comparison of linear and nonlinear subspacebased anomaly detection algorithms. Using a dual-window technique to separat...

Complexity pursuit is an extension of projection pursuit to time series data and the method is closely related to blind separation of time-dependent source signals and independent component analysis (ICA). In this paper, we consider the estimation of the data model of ICA when Gaussian noise is present and the independent components are time dependent. We derive a simple algorithm combining Gau...

Orthogonal subspace projection (OSP) is a versatile hyperspectral imaging technique which has shown great potential in dimensionality reduction, target detection, spectral unmixing, etc. However, due to its inherent requirement of prior knowledge, OSP not been explored anomaly detection. This article takes advantage an unsupervised OSP-based algorithm, automatic generation process (ATGP), and r...

The computation of the geometric transformation between a reference and a target image, known as image registration or alignment, corresponds to the projection of the target image onto the transformation manifold of the reference image (the set of images generated by its geometric transformations). It often takes a nontrivial form such that exact computation of projections on the manifold is di...